Field of the Invention
The present invention generally relates to a method, a system, one or more computational units, and a computer program product for non-invasive biometrical identification of animals, particularly a method, a system, and a computer program product using minutiae based skin markings in combination with physical characteristics for non-invasive biometrical identification of animals.
Description of the Prior Art
Farm animal identification is a major requirement for government agricultural authorities, facilitating registration of animals, recording of authorized animal movements, herd management, and payments of appropriate grants and subsidies and as a vital tool in tracing diseases of public and animal health concern. Furthermore, farmers and integrated food suppliers even retailers have requirements for specific traceability of their animal products to identify growth characteristics on an individual basis as well as identification of the food animal origins for history of feed and feed ingredients, disease and treatment details.
Most identification schemes are based on a computer database of ear-tag numbers. A potential limitation of such systems has been their tracking of a device attached to the animal, rather than tracing the animal itself. This becomes problematic when accidental loss or fraudulent switching of tags occurs, as preserving correct identification is difficult.
The more manual oriented based identification systems are generally invasive in the sense that herd separation is required for the individual to be read, analyzed and registered. It involves active participation of specialists, veterinary services and even extensive participation of mechanical machinery, equipment and boats in the case of aquaculture. The costs to enable the reading are high. Furthermore, the obvious drawback is that its data are historical, confirming the fact as they are not used continuously due to their invasive character. That is why the data collected from the traditional systems are of limited use and not specific enough to be an active tool to proactively offset actions upon abnormalities in data reading.
For aquaculture in particular, and the Atlantic salmon (Salmo salar) industry in Norway and Chile besides UK, Ireland, Faroe Islands, US, Canada, and Tasmania, as a good example, this is very obvious. The aquaculture of Atlantic salmon is an unprecedented success starting back in the early 1970ies in Norway. In 2014 the total production from the markets referred above was more than 2 million metric tons, or more than 500 million individual fish. To mark or tag each fish individually is practically impossible.
An increasing problem is escapees of cultured fish from cages that are invading and spawn with local wild species thus are polluting the local gene pool. The legislation against escapees is serious in for example Norway, with relatively high penalties for the aquaculture farmer if he can be identified to be the source of the escapees. One idea that has gained traction is to DNA identify each fish or family of fish and then conduct DNA testing of suspected escapees that are found in the rivers. The disadvantage with this method besides being costly is that the DNA testing takes too long time thus cannot proactively be used to identify other escapees, thus weed out from the waterway.
Other methods of identification are fin clipping, retina ink, and transponder insertion; however, all require a lot of handling and are expensive and also negative as far as animal welfare goes. Accordingly, a non-invasive identification and real-time monitoring system for animals is needed.